DBMS > atoti vs. GigaSpaces vs. Hawkular Metrics vs. LeanXcale vs. Yaacomo

System Properties Comparison atoti vs. GigaSpaces vs. Hawkular Metrics vs. LeanXcale vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Object oriented DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

yaacomo.com

Technical documentation

docs.atoti.io

docs.gigaspaces.com/latest/landing.html

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

ActiveViam

Gigaspaces Technologies

Community supported by Red Hat

LeanXcale

Q2WEB GmbH

Initial release

2000

2014

2015

2009

Current release

15.5, September 2020

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net

Java

Server operating systems

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-99 for query and DML statements

yes

through Apache Derby

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP REST

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

Go
Java
Python
Ruby

C
Java
Scala

Server-side scripts

Stored procedures

Python

yes

Triggers

yes, event driven architecture

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

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